Data Analysis with Python, Pandas and Visualization
Clean, analyse and visualise real-world data with Python, pandas and Matplotlib, and turn raw numbers into clear business insights.
About this course
Data analysis is one of the most in-demand skills in the modern workplace. In this course you will learn to load, clean, explore and visualise data using Python — the most widely used language for data work — together with the pandas, NumPy and Matplotlib libraries.
Every module is built around a realistic dataset, from sales records to public health statistics. You will finish with a portfolio-ready analysis project that shows employers you can ask the right questions, wrangle messy data and communicate results with clear charts and summaries.
What you'll learn
- Set up a Python data environment with Jupyter notebooks
- Load data from CSV, Excel and SQL sources into pandas
- Clean missing, duplicated and inconsistent data
- Group, aggregate and reshape data to answer business questions
- Create clear charts with Matplotlib and Seaborn
- Present findings in a portfolio-ready report
Syllabus
6 modules · 6 weeks · approx. 30 hours total
Module 1Python for data
- Jupyter notebooks
- Variables, lists and dictionaries
- Functions and loops for data tasks
Module 2Working with pandas
- Series and DataFrames
- Selecting and filtering rows
- Reading CSV, Excel and SQL data
Module 3Data cleaning
- Handling missing values
- Fixing data types and duplicates
- Working with dates and text
Module 4Exploratory analysis
- Descriptive statistics
- groupby, pivot tables and merges
- Finding trends and outliers
Module 5Data visualization
- Matplotlib fundamentals
- Statistical charts with Seaborn
- Choosing the right chart
Module 6Capstone project
- Defining an analysis question
- End-to-end analysis
- Writing up and sharing your results
Requirements & who it's for
Prerequisites
- Comfort with spreadsheets is helpful
- No prior Python experience required
Who this is for
- Aspiring data analysts
- Business professionals who work with spreadsheets
- Students preparing for data careers
Frequently asked questions
Do I need to install anything?
You can follow the whole course in a free browser-based notebook environment, or install Python locally — both options are covered.
Is this course enough to become a data analyst?
It covers the core Python skills analysts use daily. Combine it with SQL and a few portfolio projects to be job-ready.
Read before you start
SQL for Beginners: The Essential Commands Every Data Analyst Needs
A hands-on SQL tutorial covering the handful of commands that answer most real-world data questions — with copy-ready examples.
Data Analyst vs Data Scientist: Differences, Skills and Which to Choose
What each role actually does day to day, the skills and tools you need, and a simple checklist to help you choose the right data career.
How to Learn Python in 2026: A Step-by-Step Roadmap for Beginners
From installing Python to landing your first project: a realistic roadmap with timelines, project ideas and the tools professionals actually use.
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